Identification of Peculiar Data by Using Restoration Method Based on Principal Component Analysis

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概要

• 論文の詳細を見る

• 本文データは一部CiNiiから複製したものである。We have developed the restoration method for missing data based on Principal Component Analysis in the previous issues (Yuasa et al. 2005; 2006). From another point of view, this method is able to be regarded as a tool to distinguish a peculiar data from the other most of the data which can be classified normally. We show some examples in the study of classification of the stellar spectra.

• 近畿大学の論文
• 2007-02-28

著者

• SINGH Harinder

  Department of Physics and Astrophysics, University of Delhi

• Yamamoto Nawo

  Software Research Associates Inc.

• Singh Harinder

  Department Of Physics & Astrophysics University Of Delhi

• UMETANI Masafumi

  Department of Astronomical Science, The Graduate University for Advanced Studies

• Yamamoto Nawo

  Research Institute For Science And Technology Kinki University

• Umetani Masafumi

  Department Of Astronomical Science The Graduate University For Advanced Studies

• Yuasa Manabu

  Kinki Univ. Higashi‐osaka Jpn

関連論文

• Reliability Checks on the Indo-US Stellar Spectral Library Using Artificial Neural Networks and Principal Component Analysis
• Identification of Peculiar Data by Using Restoration Method Based on Principal Component Analysis
• Restoration of Missing Data and Reconstruction of Dynamical Systems
• Supplementation of Adjusted Values to the Imperfect Data

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